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Face Mask Recognition: Deep Learning based Desktop App

Learn and Build Face Recognition for Face Mask Detection Desktop App using Python, TensorFlow 2, OpenCV, PyQT, Qt
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Content

Platform: Udemy
Video: 4h 36m
Language: English
Next start: On Demand

Table of contents

Description

Project that you will be Developing:
Prerequisite of Project: OpenCV
•Image Processing with OpenCV
Section -0 : Setting Up Project
•Install Python
•Install Dependencies
Section -1 : Data Preprocessing
•Gather Images
•Extract Faces only from Images
•Labeling (Target output) Images
•Data Preprocessing
•RGB mean subtraction image
Section – 2: Develop Deep Learning Model
•Training Face Recognition with OWN Deep Learning Model.
•Convolutional Neural Network
•Model Evaluation
Section – 3: Prediction with CNN Model
1. Putting All together

Section – 4: PyQT Basics
Section -5: PyQt based Desktop Application

Overview:
I will start the course by installing Python and installing the necessary libraries in Python for developing the end-to-end project. Then I will teach you one of the prerequisites of the course that is image processing techniques in OpenCV and the mathematical concepts behind the images. We will also do the necessary image analysis and required preprocessing steps for the images. Then we will do a mini project on Face Detection using OpenCV and Deep Neural Networks.
With the concepts of image basics, we will then start our project phase-1, face identity recognition. I will start this phase with preprocessing images, we will extract features from the images using deep neural networks. Then with the features of faces, we will train the different Deep learning models like Convolutional Neural Network.  I will teach you the model selection and hyperparameter tuning for face recognition models
Once our Deep learning model is ready, will we move to Section-3, and write the code for preforming predictions with CNN model.
Finally, we will develop the desktop application and make prediction to live video streaming.
What are you waiting for? Start the course develop your own Computer Vision Flask Desktop Application Project using Machine Learning, Python and Deploy it in Cloud with your own hands.

You will learn

✓ Face Recognition for Mask detection with Deep Learning
✓ Develop Convolutional Network Network for Face Mask from Scratch using TensorFlow
✓ Preprocess the big data of image
✓ OpenCV for Face Detection
✓ Computer Vision Desktop Application with PyQt
✓ PyQt Essential Concepts

Requirements

• Basic Python Knowledge
• Familiar with Tensor Flow and Deep Learning
• Familiar with Numpy and Pandas

This course is for

• Anyone who want to develop face recognition application
Data Scientist
I am Srikanth working as Data Science with a demonstrated history of working in the information technology and services industry. Skilled in Machine Learning, Deep Learning, Statistical algorithms. We mostly worked on Image Processing and Natural Language processing application. I also successfully deployed many data science-related projects in cloud platforms as a service in AWS, Google Cloud, etc.
Platform: Udemy
Video: 4h 36m
Language: English
Next start: On Demand

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